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Exact Exponential Algorithms [recurso electrónico] / by Fedor V. Fomin, Dieter Kratsch.

Por: Fomin, Fedor V [author.]Colaborador(es): Kratsch, Dieter [author.] | SpringerLink (Online service)Tipo de material: Texto

TextoSeries Texts in Theoretical Computer Science. An EATCS SeriesEditor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2010Descripción: XIV, 206 p. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783642165337Tema(s): Computer science | Computer software | Combinatorics | Mathematical optimization | Computer Science | Algorithm Analysis and Problem Complexity | Optimization | CombinatoricsFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 005.1 Clasificación LoC:QA76.9.A43Recursos en línea: Libro electrónico Texto

Contenidos:

Branching -- Dynamic Programming -- Inclusion-Exclusion -- Treewidth -- Measure & Conquer -- Subset Convolution -- Local Search and SAT -- Split and List -- Time Versus Space -- Miscellaneous -- Conclusions, Open Problems and Further Directions.

En: Springer eBooksResumen: Today most computer scientists believe that NP-hard problems cannot be solved by polynomial-time algorithms. From the polynomial-time perspective, all NP-complete problems are equivalent but their exponential-time properties vary widely. Why do some NP-hard problems appear to be easier than others? Are there algorithmic techniques for solving hard problems that are significantly faster than the exhaustive, brute-force methods? The algorithms that address these questions are known as exact exponential algorithms. The history of exact exponential algorithms for NP-hard problems dates back to the 1960s. The two classical examples are Bellman, Held and Karp’s dynamic programming algorithm for the traveling salesman problem and Ryser’s inclusion–exclusion formula for the permanent of a matrix. The design and analysis of exact algorithms leads to a better understanding of hard problems and initiates interesting new combinatorial and algorithmic challenges. The last decade has witnessed a rapid development of the area, with many new algorithmic techniques discovered. This has transformed exact algorithms into a very active research field. This book provides an introduction to the area and explains the most common algorithmic techniques, and the text is supported throughout with exercises and detailed notes for further reading. The book is intended for advanced students and researchers in computer science, operations research, optimization and combinatorics.

Existencias ( 1 )
Notas de título ( 3 )

Existencias
Tipo de ítem	Biblioteca actual	Colección	Signatura	Copia número	Estado	Fecha de vencimiento	Código de barras
Libro Electrónico	Biblioteca Electrónica	Colección de Libros Electrónicos	QA76.9 .A43 (Browse shelf(Abre debajo))	1	No para préstamo		375336-2001

Today most computer scientists believe that NP-hard problems cannot be solved by polynomial-time algorithms. From the polynomial-time perspective, all NP-complete problems are equivalent but their exponential-time properties vary widely. Why do some NP-hard problems appear to be easier than others? Are there algorithmic techniques for solving hard problems that are significantly faster than the exhaustive, brute-force methods? The algorithms that address these questions are known as exact exponential algorithms. The history of exact exponential algorithms for NP-hard problems dates back to the 1960s. The two classical examples are Bellman, Held and Karp’s dynamic programming algorithm for the traveling salesman problem and Ryser’s inclusion–exclusion formula for the permanent of a matrix. The design and analysis of exact algorithms leads to a better understanding of hard problems and initiates interesting new combinatorial and algorithmic challenges. The last decade has witnessed a rapid development of the area, with many new algorithmic techniques discovered. This has transformed exact algorithms into a very active research field. This book provides an introduction to the area and explains the most common algorithmic techniques, and the text is supported throughout with exercises and detailed notes for further reading. The book is intended for advanced students and researchers in computer science, operations research, optimization and combinatorics.